Focused On-demand Library for Glutamate receptor ionotropic, NMDA 2A

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.


We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by Reaxense.


The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


We use our state-of-the-art dedicated workflow for designing focused libraries for receptors.


 

Fig. 1. The screening workflow of Receptor.AI

The method involves detailed molecular simulations of the receptor in its native membrane environment, with ensemble virtual screening focusing on its conformational mobility. When dealing with dimeric or oligomeric receptors, the whole functional complex is modelled, and the tentative binding pockets on and between the subunits are established to address all possible mechanisms of action.


Our library is unique due to several crucial aspects:


  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.

  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.

  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.

  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.

PARTNER
Receptor.AI
 
UPACC
Q12879

UPID:
NMDE1_HUMAN

ALTERNATIVE NAMES:
Glutamate [NMDA] receptor subunit epsilon-1; N-methyl D-aspartate receptor subtype 2A

ALTERNATIVE UPACC:
Q12879; O00669; Q17RZ6

BACKGROUND:
The Glutamate receptor ionotropic, NMDA 2A, known alternatively as N-methyl D-aspartate receptor subtype 2A, is integral to NMDA receptor complexes. These complexes, acting as heterotetrameric, ligand-gated ion channels, are vital for brain functions including learning and synaptic plasticity. Their activation, requiring glutamate and glycine, is influenced by the receptor's subunit composition, affecting glutamate sensitivity and channel kinetics.

THERAPEUTIC SIGNIFICANCE:
The therapeutic significance of the Glutamate receptor ionotropic, NMDA 2A is underscored by its association with various forms of epilepsy and related neurologic conditions. Its role in diseases characterized by seizures, intellectual disability, and speech disorders highlights the potential for targeted therapy development, aiming to modulate this receptor's function for clinical benefit.

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